Junior Quant Analyst

Federated Hermes, Inc. is a global leader in active, responsible investment management, with $911.6 AUM in assets under management, as of June 30th, 2026. We deliver investment solutions that help investors target a broad range of outcomes and provide equity, fixed income, alternative/private markets, multi-asset, and liquidity management strategies to more than 11,000 institutions and intermediaries worldwide.

Main Function of the role: The Quantitative Global Equity team combines disciplined quantitative analysis with fundamental oversight to build diversified, long-only equity portfolios that aim to deliver consistent, all-weather returns. In support of Portfolio Managers on the Quantitative Global Equity team, the Quantitative Analyst will be expected to take responsibility for developing a scalable quantitative platform, managing data pipelines, and automating recurring tasks using AI capabilities and quantitative tools.

Key tasks and responsibilities:

• Develop and maintain quantitative investment systems that support portfolio construction, security selection, risk management, trading, and performance analysis across the investment process.
• Partner with portfolio managers, investment researchers, and traders, as well as the Enterprise AI & Data Science team to translate investment ideas, models, and research prototypes into reliable, scalable, production-ready applications.
• Work with the Enterprise Data Platform team to design and manage data pipelines for market, security, portfolio, and alternative data, ensuring data quality, consistency, availability, and appropriate controls.
• Implement, test, and validate quantitative models and analytics, including backtesting frameworks, optimization tools, risk models, forecasting methods, and portfolio simulations.
• Build and enhance the firm's quantitative research and investment technology platform, with an emphasis on reusable components, automation, computational efficiency, and effective user experience.
• Maintain high standards for software engineering and production reliability through code reviews, version control, documentation, testing, monitoring, troubleshooting, and appropriate model-governance and change-management practices.

Minimum Experience Required:

• The ideal candidate will possess very strong academic credentials (particularly in maths, statistics and/or accountancy), holding a degree preferably a 2:1 or above in a STEM discipline or an advanced qualification.
• Proficient in accountancy and able to communicate clearly and succinctly in both written and oral form.
• Strong programming skills in Python, including experience with data-analysis and quantitative-computing libraries such as pandas and NumPy, along with experience using SQL and cloud-based data platforms such as Databricks.
• Ideally have a minimum of one to two years’ professional experience gained within asset management or another financial services role, with demonstrable hands-on experience in engineering quantitative systems and working with financial data.
• Knowledge of and interest in equity markets, gained through professional experience, personal investing, or academic study.

Candidate Profile:

• Foundational knowledge of software-engineering practices, including writing clear and maintainable code, using version control, developing tests, documenting work, and debugging technical issues.
• Experience working with structured datasets, including data preparation, validation, analysis, and the development of repeatable data-processing workflows.
• Working knowledge of quantitative methods, including statistics, regression analysis, time-series concepts, optimization, or model evaluation, with attention to numerical accuracy and the reliability of analytical outputs.
• Working knowledge of investment management concepts is preferred, including portfolio construction, financial markets, and risk analysis, with the ability to apply this knowledge in partnership with portfolio managers and researchers.
• Effective communication and collaboration skills, including the ability to work closely with portfolio managers, quantitative researchers, risk professionals, data teams, and technology colleagues and to explain technical concepts to non-technical stakeholders.

Diversity, Inclusion and Flexible Working: We believe in genuine opportunity, fairness, and respect for all applicants and aim to ensure that no current or prospective employee is subject to discrimination or treated less favourably on the basis of their disability, gender identity or expression, race, ethnicity, religion or belief, marriage or civil partnership, pregnancy and maternity, age, sex, or sexual orientation, or disability. We understand that applicants may have different needs and expectations related to their working arrangements and are committed to a discussion on flexible working.

We welcome applications from all eligible candidates, and we particularly encourage applications from qualified candidates who identify as women and/or are from a Black, Asian and Minority Ethnic background, as these groups are underrepresented throughout the financial services sector.

We are a Disability Confident Employer and participate in the 'Offer of Interview' scheme, intended to actively encourage applications from people with a disability or long-term condition and offer an interview to those who meet the minimum criteria set out within this job description.